Artificial intelligence-based control system for the analysis of metal casting properties

• Autorzy: Mares E. , Sokolowski J. H.
• Języki publikacji: EN

Abstrakty

EN

Purpose: The metal casting process requires testing equipment that along with customized computer software properly supports the analysis of casting component characteristic properties. Due to the fact that this evaluation process involves the control of complex and multi-variable melting, casting and solidification factors, it is necessary to develop dedicated software. Design/methodology/approach: The integration of Statistical Process Control methods and Artificial Intelligence techniques (Case-Based Reasoning) into Thermal Analysis Data Acquisition Software (NI LabView) was developed to analyze casting component properties. The thermal data was tested in terms of accuracy, reliability and timeliness in order to secure metal casting process effectiveness. Findings: Quantitative values were defined as “Low”, “Medium” and “High” to assess the level of improvement in the metal casting analysis by means of the Artificial Intelligence-Based Control System (AIBCS). The traditional process was used as a reference to measure such improvement. As a result, the accuracy, reliability and timeliness were significantly increased to the “High” level. Research limitations/implications: Presently, the AIBCS predicts a limited number of casting properties. Due to its flexible design more properties could be added. Practical implications: The AIBCS has been successfully used at the Ford/Nemak Windsor Aluminum Plant (WAP) to analyze Al casting properties of the engine blocks. Originality/value: The metal casting research community has immensely benefited from these developed information technologies that support the metal casting process.

Słowa kluczowe

EN

casting; artificial intelligence method; metallurgy; statistical process control

PL

odlewnictwo; metoda sztucznej inteligencji; metalurgia; sterowanie procesem statystyczne

• Wydawca: International OCSCO World Press
• Czasopismo: Journal of Achievements in Materials and Manufacturing Engineering
• Rocznik: 2010
• Tom: Vol. 40, nr 2
• Strony: 149--154
• Opis fizyczny: Bibliogr. 13 poz., rys., tabl.

Twórcy

autor

Mares E.

autor

Sokolowski J. H.

• Metal Casting Technology Group, University of Windsor, 218 Essex Hall, 401 Sunset Avenue, Windsor, Ontario N9B 3P4, Canada,

Bibliografia

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